See Through Walls with Wi-Fi!

Review & PResentation

See Through Walls with Wi-Fi! Fadel Adib and Dina Katabi Massachusetts Institute of Technology SIGCOMM’13, August 12–16, 2013, Hong Kong, China

outline

outline Background ~ Motivation & Previous work ~ The Big Picture, Challenges & Application Research Solution & Design ~ Basic idea - WIVI ~ How to eliminate ~ How to track Demo & Gesture Interface Implementation & Experimental Results Concluding Remarks & Future works

Can youR CellPhone give you XRay vision?

PRevious woRk

• Designed for military [RCP10] – 2 GHz bandwidth – Large power source – Huge antenna array • Attempt at using Wi-Fi [CSW12] – Needs to install a receiver in the imaged room and connect it to a receiver outside the room via wire

8 feet

the Big PiCtuRe

x αx

h1

h2

Challenges

Wall refection is 10,000x stronger than reflections coming from behind the wall

Tracking people from their reflections

aPPliCations Police avoids ambush

Personal security

Firefighters check for humans

Gesture interface from behind a wall

outline Background ~ Motivation & Previous work ~ The Big Picture, Challenges & Application Research Solution & Design ~ Basic idea - WIVI ~ How to eliminate ~ How to track Demo & Gesture Interface Implementation & Experimental Results Concluding Remarks & Future works

wi-vi: wiFi vision -- small, low-PoweR, Cost • • • • • •

Eliminate the wall’s reflection Detect and track people from reflections Gesture-based interface Implemented on software radios Wi-Vi uses Wi-Fi signals to see through walls Identify the number of moving humans and their relative locations • Allows humans to communicate without a transmitting device • Through-wall gesture based interface

Flash eFFeCt

Reflections off the wall overwhelm the receiver’s analog to digital converter, preventing it from registering the minute variations due to reflections from objects behind the wall. This behavior is called the “Flash Effect"

two main Challenges

two main Challenges

how Can we eliminate the wall’s ReFleCtion?

BasiC idea:

Transmit two waves that cancel each other when they reflect off static objects but not moving objects

Wall is static

disappears

People tend to move

detectable

eliminating the wall’s ReFleCtion Receive Antenna:

x Îąx

Transmit Antennas

eliminating the wall’s ReFleCtion Receive Antenna:

x

y = h1 x + h2αx

h1

α = -h1 / h2

αx

h2

0

eliminating all statiC ReFleCtions

eliminating all statiC ReFleCtions x αx

h1

y = h1 x + h2αx h2

Static objects (wall, furniture, etc.) have constant channels

y = h1 x + h2(- h1/ h2)x

0

People move, therefore their channels change y = h1’ x + h2’(- h1/ h2)x

Not Zero

how Can we tRaCk using ReFleCtions?

tRaCking motion

RF source

θ

Direction of reflection

Antenna Array

tRaCking motion Direction of motion

θ At any point in time, we have a single measurement

Antenna Array

tRaCking motion Direction of motion

θ θ Direction of motion Antenna Array

tRaCking motion Direction of motion

θ θ Direction of motion

Human motion emulates antenna array Antenna Array

outline Background ~ Motivation & Previous work ~ The Big Picture, Challenges & Application Research Solution & Design ~ Basic idea - WIVI ~ How to eliminate ~ How to track Demo & Gesture Interface Implementation & Experimental Results Concluding Remarks & Future works

a thRough-wall gestuRe inteRFaCe

• Sending Commands with Gestures • Two simple gestures to represent bit ‘0’ and bit ‘1’ • Can combine sequence of gestures to convey longer message

gestuRe enCoding

Bit ‘0’: step forward followed by step backward Bit ‘1’: step backward followed by step forward Step Forward

Step Backward

gestuRe deCoding Matched Filter

0

2

4

6 8 T im e (S e c o n d s)

10

12

14

Peak Detector Bit ‘0’

Bit ‘1’

Gesture interface that works through walls and none-line-of-sight 0

2

4

6 8 Time (Seconds)

10

12

1

outline Background ~ Motivation & Previous work ~ The Big Picture, Challenges & Application Research Solution & Design ~ Basic idea - WIVI ~ How to eliminate ~ How to track Demo & Gesture Interface Implementation & Experimental Results Concluding Remarks & Future works

imPlementation and evaluation

• USRP software radios: – Wi-Fi signals: 2.4GHz, OFDM – 5MHz to enable real-time channel estimation – 10mW transmit power

• Old and new buildings on MIT campus • Eight human subjects – 200 experiments

tRaCking multiPle humans

One moving person is indicated by a single curvy line

tRaCking multiPle humans

• Number of distinct curves at the same time corresponds to the number of humans Two Humans

100

60

60

40

40

20 0 -20 -40 -60

2

20 0 -20 -40 -60

-80 -100

1

80

Angle (degrees)

Angle (degrees)

100

2

80

Three Humans

1 0

1

2

3

-80 3 4 Time (seconds)

5

6

7 -100 0

1

2

3 4 Time (seconds)

5

6

7

automatiC estimation: numBeR oF PeoPle

Detected

0

1

2

3

0

100%

0%

0%

0%

1

0%

100%

0%

0%

2

0%

0%

85%

15%

3

0%

0%

10%

90%

Actual

Building mateRials 100

100

100

100

100 87.5

Accuracy (%)

80 60 40 20 0

Free Space

1.75 wood door

8 concrete

gestuRes: aCCuRaCy vs. distanCe Bit '0'

Bit '1'

Accuracy (%)

100 80 60 40 20 0

1

2

3

4

5

6

7

Distance from the wall (meters)

8

9

ConClusion Wi-Vi bridges advance networking techniques with human-computer interaction.

It motivates a new form of user interfaces which rely solely on using the reflections of a transmitted RF signal to identify human gestures.

More improvements will further allow Wi-Vi to capture higher quality images enabling the gesturebased interface to become more expressive hence promising new directions for virtual reality

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